NRT-AI: Graduate Training in Translational Convergent Research - Harnessing AI and Data Science for Sustainable Agriculture (GRAD-AID for Ag)

Mitigating the impact of global climate change on sustainable agriculture and, consequently food production depends on our ability to cultivate plants that tolerate increasing heat, drought, and extreme weather events while requiring fewer resources for growth. Advances in both fundamental and applied research have driven key innovations in plant science; however, fundamental discoveries in the lab rarely hold up under dynamic field conditions.

Thus, they fall short of meeting the escalating demand for effective translatable solutions. The application of Artificial intelligence (AI), machine learning (ML), and other data-driven approaches to the wealth of data generated by fundamental and applied plant scientists offers potential solutions to this problem. However, cross-domain data analytics remain underutilized due to historical disciplinary silos that limit student training.

This National Science Foundation Research Traineeship award to North Carolina State University will, in partnership with Fayetteville State University, train twenty-one (21) doctoral students, including ten (10) NSF-funded trainees, at the convergence of plant science and AI to accelerate the translation of knowledge from lab to field to market.

The potential of AI and ML to facilitate translational plant science offers a fertile learning environment for transdisciplinary graduate training. Within this traineeship, collaborative graduate student cohort training approaches will be used, engaging diverse students from plant science, data and computer science, and engineering graduate programs.

Cohorts will be challenged to complete user-inspired capstone research projects in partnership with local growers and cross-disciplinary faculty advisor teams over two years. These partnerships, facilitated by on-farm learning experiences, an interdisciplinary orientation boot camp, industry internships, and community outreach, will provide an immersive learning environment that enhances students’ abilities to identify and tackle real world challenges at the intersection of basic and applied plant science and AI.

A convergent curriculum will increase student proficiency and core competency in these areas, while also educating students on the societal implications, impacts, concerns, and risks associated with applying AI and ML to agriculture. Research, teaching, and academic partnerships with minority serving institutions will enable the future development of a new bridge to the doctorate training program that increases the presence of those underrepresented in plant sciences and engineering.

To address the grand challenge of sustainable agriculture and global food security, this training program will create a diverse, interdisciplinary workforce empowered to engage with industry, grower, and academic partners.

The NSF Research Traineeship (NRT) Program will bring together graduate students from multiple disciplines interested in design and engineering for sustainability to solve real-world problems and increase climate resilience. This project will offer students not only core technical education and training opportunities but important soft skills to become inclusive and responsible future workforce.

It will foster collaborations and support immersive experiences for trainees and build a diverse community in STEAM fields.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.